We are pleased to announce the Innovation Catalysts grant recipients for the fall semester! The Jacobs Institute Innovation Catalysts is a grant program that helps Berkeley’s student innovators unlock potential in their projects. Over the semester, grant winners will work on their projects with the support of funding and mentorship from Jacobs Hall and the CITRIS Invention Lab. Recipients will receive a Maker Pass and have access to all of our Makerspace resources, in addition to on-going mentorship from our Student Advisory Board, Jacobs Technical Staff, Design Fellows, and others.
This fall, eight projects were selected by our Student Advisory Board and leadership team to be part of the grant program. Five groups were selected for our Ignite grant, which awards student groups up to $2000 to continue in-progress projects; and three groups were selected for our Spark grant, which offers up to $500 for early-stage project ideas.
This semester’s cohort includes a wide range of Jacobs students, from freshman to our MDes cohort; with many students addressing the rising issues from COVID-19. Learn more about each group and project scope below, and make sure to join us for our Design Showcase, December 8 + 9, to learn how each group’s projects developed over the course of the semester.
Advanced Imaging Tools with Rapid and Efficacious T Cell Labeling to Bring CAR-T Cell Immunotherapies to Patients with Solid Tumors
Renesmee Kuo (Bioengineering, 2022)
Tracking CAR-T cells using Magnetic Particle Imaging with high sensitivity, made possible by a millifluidic technology that isolates and labels T cells, Kuo’s project sets out to revolutionize immunotherapies for patients with solid tumors. Kuo’s end goal is to present a fully functional and meticulously crafted millifluidic technology that fractionates different blood cell components by their relative size and differences in specific gravity.
Balance Board Math
Sofia Tancredi (Special Education, 2023), Helen Li (Master of Information Management & Systems, 2022), Julia Wang (B.S. Electrical Engineering and Computer Sciences, 2022)
Balance Board Math is an inclusive math education platform that enables children to explore math concepts through their sense of balance using movement such as fidgeting, rocking, etc. Research shows that this kind of movement, often considered disruptive in traditional classrooms, might reflect an underlying need for sensory stimulation, and that movement like rocking can actually support a learner’s self regulation, attention, and memory. Balance Board Math allows kids to use spontaneous movement as part of their math instruction by rocking on a balance board to explore different mathematical activities.
X Sun (Mechanical Engineering ’22)
Bear Air’s goal is to build customized, low-cost, accessible air purifying devices. The devices will use high flow-rate air blowers and moderately graded, but more attainable, filters for low-income student communities. The ability to distribute the devices in student residence and cooperative houses will improve indoor air quality, especially in the face of COVID Delta Variant and the pendingand pending fire season. So far, the team’s preliminary testing data has proved their device to be more economically efficient than the current commercial air purifiers on the market.
Ryan Mei (Electrical Engineering and Computer Science, Business Administration 2023), Will Panitch (Electrical Engineering and Computer Science, Cognitive Science 2023)
Nanodext is a desktop cell manipulation robot designed to image, grasp, move, and inject thousands of cells per minute with nanometer precision in 3D. Nanodext is capable of executing a variety of genetic, cell, and tissue engineering workflows, which traditionally take weeks, in a matter of hours, while replacing a room full of equipment. At the core of the Nanodext system is a combination of advanced light-field imaging and nanorobotic techniques that allow their system to achieve an unprecedented level of precision and speed.
Yuting Wang (Master of Design, 2022)
Smell Revived is the first Virtual Reality smell training system targeting post-COVID smell dysfunction. The aim of Yuting’s project is to help patients with smell dysfunction—parosmia and anosmia, to name a few examples—better recover through the means of smell training. Provided a more thorough visual stimulation in virtual reality, patients can better retrain their brain and nose to recognize those smells. Bringing VR to smell therapy will make the therapeutic experience more fun, engaging, and ultimately effective.
Cameron Chaney (Mechanical Engineering 2023)
BudE is a crash detection system designed to keep cyclists safe while riding alone in the deep outdoors, minimizing the danger of a cyclist falling alone. The detachable device continuously senses for crashes, notifying emergency personnel via satellite communication if a rider is unresponsive for a given amount of time.
Development of an Affordable Brushless Motor Controller for Small Scale Robotics Applications
Sohom Roy (Mechanical Engineering Major, EECS Minor, 2025)
The goal of Roy’s project is to develop a BLDC (Brushless DC) motor controller with closed loop control capabilities, that allow the control of these motors at a low cost. Increasing access to the tools needed to prototype or build small scale versions of advanced robotics technologies will benefit students, hobbyists, and researchers with limited funds. The improvements BLDC motors present over traditional brushed DC motors mean they are much more suitable for applications such as prosthetics, mechanisms that augment the strength of humans, and in mobile robotics, but access to them is usually cost prohibitive.
Hailey Garcia (M.E.T. EECS & Business , 2025), Yuridia Vargas Perez (BioEngineering, 2025)
FairAir works to spread awareness about the health issues and disparities in low-income communities as a result of poor air quality. The team’s product connects sensors that display the air quality in areas with historically bad air quality to street lamps, alerting people about the current safety of their air quality using color-coded signals.